Systems and methods for co-expression analysis in immunoscore computation

Abstract

Described herein are methods for co-expression analysis of multiple markers in a tissue sample comprising: computing a heat map of marker expression for each of a plurality of single marker channel images, wherein each of the plurality of single marker channel images comprise a single marker; identifying one or more candidate regions of interest in each heat map of marker expression; computing overlay masks comprising the identified one or more candidate regions of interest from each heat map of marker expression; determining one or more co-localized regions of interest from the overlay masks; mapping the one or more co-localized regions of interest to a same coordinate position in each of the plurality of single marker channel images; and estimating a number of cells in at least one of the determined one or more co-localized regions of interest in each of the plurality of single marker channel images.

Description

CROSS REFERENCE TO RELATED APPLICATIONS[0001]This patent application is a continuation of International Patent Application No. PCT / EP2015 / 081399 filed Dec. 30, 2015, which claims priority to and the benefit of U.S. Provisional Application No. 62 / 098,075, filed Dec. 30, 2014 and U.S. Provisional Application No. 62 / 253,179, filed Nov. 10, 2015. Each of the above patent applications is incorporated herein by reference as if set forth in its entirety.BACKGROUND[0002]In the analysis of biological specimens, the specimens are often stained with one or more combinations of stains or assays, and the stained biological specimen is viewed or imaged for further analysis. Observing the assay enables a variety of processes, including diagnosis of disease, assessment of response to treatment, and development of new drugs to fight disease.[0003]Multiplex staining is a technique for the detection of multiple biomarkers within a single tissue section and has become more popular due to its significan...

AI Technical Summary

Benefits of technology

This method provides reproducible and objective results for co-expression analysis, reducing human subjectivity and improving the accuracy and efficiency of immunoscore computation by automating the identification and counting of immune cells in tissue samples.

Problems solved by technology

Manual selection of the FOVs or ROIs and counting is highly subjective and biased to the readers, as different readers may select different FOVs or ROIs to count.

Hence, an immunoscore study is not necessarily reproducible.

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